Image processing device, image processing program and image processing method, and image transmission/reception system and image transmission/reception method

ABSTRACT

The image processing device comprises: a filter coefficient storage means in which a filter coefficient is stored; a means for executing filtering processing to subject input image data to filtering and generate a first image data; a means for executing convolution processing to use the filter coefficient stored by the filter coefficient storage means, carry

TECHNICAL FIELD

The present invention relates to an image processing device, an imageprocessing program, and an image processing method.

BACKGROUND ART

A method employing a generalized inverse filter, the Richardson-Lucymethod (referred to hereafter as the “RL method”), and so on are knownas conventional image restoration techniques for restoring degradedimages (Non-Patent Document 1). In these methods, it is assumed that thedegradation process is known, and the restored image to be achieved isdetermined so as to minimize a square error between an input image andan image that has been degraded by the degradation process.

A generalized inverse filter calculates an inverse matrix through thesolution of the conditions required to minimize the square error. As is,the calculation is often difficult, and therefore the discrete Fouriertransform is implemented in order to perform the calculation in afrequency domain, whereupon the calculation result is transformed backto the real domain. This is dependent on the inverse matrix calculationin the frequency domain being division. In the RL method, a restoredimage having a minimum square error is acquired using an iterativemethod so as to gradually converge on a true solution from an initialsolution.

In Patent Document 1, a method of executing the calculation in each of aplurality of local regions of a degraded image, using filtercoefficients corresponding to the local regions, is proposed with theaim of reducing a processing amount when restoring the degraded image.

CITATION LIST Patent Document

Patent Document 1: Patent Publication JP-A-2010-61541

Non-Patent Document

Non-Patent Document 1: M. R. Banham and A. K. Katsaggelos, “DigitalImage Restoration”, IEEE Signal Processing Magazine, pp. 24-41, 1997

SUMMARY Technical Problem

With the conventional techniques described above, however, an increasein the calculation amount is unavoidable.

The present invention has been designed in consideration of thesecircumstances, and an object thereof is to provide an image processingdevice, an image processing program, and an image processing method withwhich a calculation amount can be reduced.

Solution to Problem

An image processing device according to an aspect of the presentinvention includes filter coefficient storing means storing a filtercoefficient, means for executing filtering processing to generate firstimage data by performing filtering on input image data, means forexecuting convolution processing to generate second image data byperforming a convolution calculation on the first image data using thefilter coefficient stored in the filter coefficient storing means, meansfor executing division processing to generate third image data bydividing the first image data by the second image data, and means forexecuting multiplication processing to generate output image data bymultiplying the third image data by the first image data.

The image processing device described above further includes means forexecuting the convolution processing, the division processing, and themultiplication processing repeatedly.

Further, in the image processing device described above, the filterstoring means stores a plurality of filter coefficients, and the meansfor executing the convolution processing uses a different filtercoefficient, among the plurality of filter coefficients, each time theconvolution processing is executed thereby.

Furthermore, an image processing program according to another aspect ofthe present invention causes a computer to execute the steps of:executing filtering processing to generate first image data byperforming filtering on input image data; executing convolutionprocessing to generate second image data by reading a filter coefficientstored in a filter coefficient storage unit and performing a convolutioncalculation on the first image data; executing division processing togenerate third image data by dividing the first image data by the secondimage data; and executing multiplication processing to generate outputimage data by multiplying the third image data by the first image data.

Moreover, an image processing method according to a further aspect ofthe present invention includes the steps of: executing filteringprocessing to generate first image data by performing filtering on inputimage data; executing convolution processing to generate second imagedata by reading a filter coefficient stored in a filter coefficientstorage unit and performing a convolution calculation on the first imagedata; executing division processing to generate third image data bydividing the first image data by the second image data; and executingmultiplication processing to generate output image data by multiplyingthe third image data by the first image data.

Advantageous Effects of Invention

According to the present invention, optimal image processing can beperformed, and as a result, an image having a higher resolution can beacquired and the calculation amount can be reduced.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a schematic view of an image processing system 1 according toan embodiment of the present invention.

FIG. 2 is a conceptual diagram of an image processing device 10according to a first embodiment.

FIG. 3 is a conceptual diagram of the image processing device 10according to a second embodiment.

FIG. 4 is a conceptual diagram of the image processing device 10according to a third embodiment.

FIG. 5 is a conceptual diagram of a medical video processing system 2 towhich the image processing device 10 is applied.

FIG. 6 shows an image prior to image processing by the medical videoprocessing system 2 and a frequency spectrum thereof.

FIG. 7 shows an image following image processing by the medical videoprocessing system 2 and the frequency spectrum thereof.

FIG. 8 is a conceptual diagram of an image transmission/reception system3 to which the image processing device 10 is applied.

DESCRIPTION OF EMBODIMENTS

Embodiments of the present invention will be described below withreference to the figures.

FIG. 1 is a schematic view showing an image processing system 1according to an embodiment of the present invention. The imageprocessing system 1 includes an image processing device 10, an imagingcamera 20, and a display device 30. The imaging camera 20 generatesinput image data representing a captured image of a predeterminedimaging subject and transmits the generated data to the image processingdevice 10. The image processing device 10 performs predeterminedprocessing on the input image data received from the imaging camera 20and transmits output image data to the display device 30. The displaydevice 30 displays a predetermined image on the basis of the outputimage data received from the image processing device 10.

FIG. 2 is a conceptual diagram of the image processing device 10according to a first embodiment. The image processing device 10 includesan image data acquisition unit 100, a filter coefficient storage unit200, an image processing unit 300, and an image data output unit 400.Note that the image processing device 10 may further include meansprovided in a normal image processing device, such as night visioncorrecting means, in addition to the configurations/functions describedin the respective embodiments.

The image data acquisition unit 100 acquires image data acquired byturning a predetermined image into digital data. The image dataacquisition unit 100 may download the image data from a medium such as aCD-ROM or a DVD, or may acquire the image data via a USB cable, Wi-Fi,the Internet, a broadcasting network, and so on, for example. Further,the image data acquisition unit 100 is not limited to means foracquiring image data from the outside of the image processing device 10,and instead, the image data acquisition unit 100 itself may beconstituted by imaging means such as a camera.

The filter coefficient storage unit 200 stores a point spread filtercoefficient (referred to hereafter as a “PSF coefficient”), which servesas an example of a filter coefficient, for each pixel of the input imagedata to be subjected to image processing. Note that the PSF coefficientsmay be, for example, estimated from optical system parameters,experiments, and so on, or predetermined coefficients may be set inadvance. The PSF coefficients corresponding to the respective pixels maybe configured such that a plurality of patterns of coefficient valuesare stored for each pixel.

The image processing unit 300 includes a filtering processing unit 310,a convolution processing unit 320, a division processing unit 330, and amultiplication processing unit 340. The image processing unit 300performs predetermined processing on the input image data, therebygenerating the output image data. The respective configurations includedin the image processing unit 300 will be described in detail below.

The image data output unit 400 outputs the output image data. The imagedata output unit 400 may, for example, write the image data to a mediumsuch as a CD-ROM or a DVD, or may output the image data to a USB cable,Wi-Fi, the Internet, a broadcasting network, and so on. Further, theimage data output unit 400 is not limited to means for outputting imagedata to the outside of the image processing device 10, and instead, theimage data output unit 400 itself may be constituted by image displaymeans such as a monitor.

Next, the image processing performed by the image processing device 10will be described briefly.

First, the image data acquisition unit 100 acquires input image data G(x, y) and transmits the acquired data to the filtering processing unit310. Here, G (x, y) is a pixel value relating to a brightness atcoordinates (x, y) indicating the position of a point within the inputimage data. In the input image data, the coordinates (x, y) may includea plurality of types of pixel values relating to color and so on as wellas brightness, but in this case, a similar description to the aboveapplies.

The filtering processing unit 310 generates first image data A_(k) (x,y) by performing blurring processing on the input image data G (x, y).As the blurring processing, the filtering processing unit 310 mayexecute filtering processing using a well-known filter such as aGaussian filter, or may read the PSF coefficients from the filtercoefficient storage unit 200 and execute filtering processing using thePSF coefficients. By executing this filtering processing, the inputimage data are smoothed, and as a result, an increase in noise caused bysubsequent processing can be suppressed.

An arithmetic expression of the processing performed by the filteringprocessing unit 310 is shown in formula (1). Note that S_(k) (i, j)denotes a filter function.

A _(k) (x, y)=G (x, y)*S (i, j)   (1)

Note that the image data acquisition unit 100 may transmit the inputimage data G (x, y) directly to the convolution processing unit 320. Inthis case, the first image data A_(k) (x, y) are the input image data G(x, y). Whether to have the image data acquisition unit 100 transmit theinput image data G (x, y) to the filtering processing unit 310 or to theconvolution processing unit 320 may be selected as appropriate inaccordance with a predetermined determination condition.

The convolution processing unit 320 generates second image data B_(k)(x, y) by reading the PSF coefficient P_(k) (i, j) stored in the filtercoefficient storage unit 200 and executing a convolution calculationusing the PSF coefficient on the first image data A_(k) (x, y). In otherwords, the convolution processing unit 320 generates the second imagedata by performing a type of filtering on the first image data.

An arithmetic expression of the processing performed by the convolutionprocessing unit 320 is shown in formula (2).

B _(k) (x, y)=A _(k) (x, y)*P _(k) (i, j)   (2)

The division processing unit 330 generates third image data C_(k) (x, y)by dividing the first image data A_(k) (x, y) by the second image dataB_(k) (x, y). In other words, the division processing unit 330 generatesthird image data representing a ratio of the first image data to thesecond image data for each pixel. This ratio correlates to each pixelvalue of the original first image data, and therefore parts of the firstimage data corresponding to edges, for example, have different ratios toother parts.

An arithmetic expression of the processing performed by the divisionprocessing unit 330 is shown in formula (3).

$\begin{matrix}\begin{matrix}{{C_{k}\left( {x,y} \right)} = {{A_{k}\left( {x,y} \right)}/{B_{k}\left( {x,y} \right)}}} \\{= {{A_{k}\left( {x,y} \right)}/\left( {{A_{k}\left( {x,y} \right)}*{P_{k}\left( {i,j} \right)}} \right)}}\end{matrix} & (3)\end{matrix}$

The multiplication processing unit 340 generates output image data F_(k)(x, y) by multiplying the third image data C_(k) (x, y) by the firstimage data A_(k) (x, y).

An arithmetic expression of the processing performed by themultiplication processing unit 340 is shown in formula (4).

$\begin{matrix}\begin{matrix}{{F_{k}\left( {x,y} \right)} = {{A_{k}\left( {x,y} \right)} \times {C_{k}\left( {x,y} \right)}}} \\{= {{A_{k}\left( {x,y} \right)} \times \left( {{A_{k}\left( {x,y} \right)}/\left( {{A_{k}\left( {x,y} \right)}*{P_{k}\left( {i,j} \right)}} \right)} \right)}}\end{matrix} & (4)\end{matrix}$

The output image data F_(k) (x, y) generated by the multiplicationprocessing unit 340 are transmitted to the image data output unit 400and output thereby.

Note that in the processing described above, parallel processing may beexecuted as appropriate using a plurality of processing lines, andprocessing such as bit shifting may also be executed as appropriate.

Next, a second embodiment of the image processing device 10 will bedescribed. Note that from the second embodiment onward, description ofelements included in the first embodiment will be omitted, and onlypoints that differ from the first embodiment will be described. Inparticular, similar actions and effects brought about by similarconfigurations will not be described repeatedly in each embodiment.

FIG. 3 is a conceptual diagram of the image processing device 10according to the second embodiment. The image processing unit 300 of theimage processing device 10 includes, in addition to the filteringprocessing unit 310, convolution processing units 320 to 323, divisionprocessing units 330 to 333, and multiplication processing units 340 to343. In other words, a feature of the second embodiment of the presentinvention is that the convolution processing, division processing, andmultiplication processing of the first embodiment are executedrepeatedly. More specifically, the second embodiment is configured suchthat the convolution processing unit, the division processing unit, andthe multiplication processing unit of the first embodiment are connectedin series in a plurality of stages.

Note that in the second embodiment, the convolution processing, divisionprocessing, and multiplication processing are connected in series infour stages, but this is merely an example, and the respectiveprocessing units may be connected in a desired number of stages.Moreover, the processing that is executed repeatedly is not limited tothe convolution processing, division processing, and multiplicationprocessing, and other processing, including the filtering processing,may also be executed repeatedly as appropriate.

In the image processing device 10, the filtering processing unit 310executes filtering processing on the input image data input therein.Next, the convolution processing unit 320, the division processing unit330, and the multiplication processing unit 340 execute processing onthe image data subjected to filtering processing by the filteringprocessing unit 310. The image data generated by the multiplicationprocessing unit 340 are then transmitted to the convolution processingunit 321, whereupon the convolution processing unit 321, the divisionunit 331, and the multiplication unit 341 respectively executeprocessing thereon. In the second embodiment, the processing is executedfour times, whereupon the output image data generated by themultiplication processing unit 343 are transmitted to the image dataoutput unit 400.

Next, a third embodiment of the image processing device 10 will bedescribed.

FIG. 4 is a conceptual diagram of the image processing device 10according to the third embodiment. The image processing device 10includes, in addition to the filtering processing unit 310, theconvolution processing unit 320, the division processing unit 330, andthe multiplication processing unit 340. The image processing device 10further includes a determination unit 350 and a buffer 360. A feature ofthe third embodiment is that the convolution processing, divisionprocessing, and multiplication processing of the first embodiment areexecuted repeatedly. More specifically, the third embodiment isconfigured such that the convolution processing unit, the divisionprocessing unit, and the multiplication processing unit of the firstembodiment are connected in a loop.

In the image processing device 10, the filtering processing unit 310executes filtering processing on the input image data input therein.Next, the convolution processing unit 320, the division processing unit330, and the multiplication processing unit 340 execute processing onthe image data subjected to filtering processing by the filteringprocessing unit 310. The determination unit 350 then determines whetheror not iterative processing by the convolution processing unit 320, thedivision processing unit 330, and the multiplication processing unit 340has been performed a predetermined number of times. When a predeterminednumber of iterations has not yet been reached, the image data generatedby the multiplication processing unit 340 are stored in the buffer 360.The convolution processing unit 320, the division processing unit 330,and the multiplication processing unit 340 then respectively executefurther processing on the image data stored in the buffer 360. When thepredetermined number of iterations is reached, the image data generatedby the multiplication processing unit 340 are transmitted to the imagedata output unit 400 as the output image data.

When a series arrangement is employed, as in the second embodiment,there is no need to provide a buffer, and therefore processing forwriting data to the buffer and reading data from the buffer isunnecessary, leading to an increase in processing speed. Conversely,when iterative processing is employed, as in the third embodiment, areduction in circuit scale can be achieved.

In the second and third embodiments, different configurations areemployed, as described above, but identical calculations are executed.More specifically, in the second and third embodiments, the processingshown in formulae (2) to (4) is executed repeatedly, but as indicated byformula (5), the image data F_(k) (x, y) generated by the multiplicationprocessing unit during k^(th) processing becomes A_(k+1) (x, y), whichserves as the input of k+1^(th) processing by the convolution processingunit, and therefore F_(k) (x, y) and F_(k+1) (x, y) are related asindicated by formula (6).

A _(k+1)(x, y)=F _(k)(x, y)   (5)

F_(k+1)(x, y)=F_(k)(x, y)×(F_(k)(x, y)/(F_(k)(x, y)*P_(k+1)(i, j)))  (6)

Note that the filter coefficient storage unit 200 may store a pluralityof patterns of PSF coefficient values for each pixel, and in this case,during the iterative processing described above, different PSFcoefficients, among a plurality of patterns of PSF coefficient values,are used each time the convolution processing is executed.

Exemplary embodiments of the image processing device 10 were describedabove. The first embodiment includes filter coefficient storing meansstoring a filter coefficient, means for executing filtering processingto generate first image data by performing filtering on input imagedata, means for executing convolution processing to generate secondimage data by performing a convolution calculation on the first imagedata using the filter coefficient stored in the filter coefficientstoring means, means for executing division processing to generate thirdimage data by dividing the first image data by the second image data,and means for executing multiplication processing to generate outputimage data by multiplying the third image data by the first image data.Thus, optimum image processing can be performed, and as a result, animage having a higher resolution can be acquired and the calculationamount can be reduced.

The second and third embodiments further include means for executing theconvolution processing, division processing, and multiplicationprocessing repeatedly. As a result, the resolution of the image can beimproved even further.

Next, example applications of the image processing device 10 accordingto the first to third embodiments will be described.

FIG. 5 is a conceptual diagram of a medical video processing system 2 towhich the image processing device 10 is applied. The medical videoprocessing system 2 includes the image processing device 10, a medicalcamera 21, and a medical monitor 31. Here, the medical camera 21 is anendoscope camera or the like, for example. The image processing device10 processes input image data input therein from the medical camera 21,and outputs the processed data to the medical monitor 31. The medicalmonitor 31 outputs video or the like required by doctors whileimplementing medical practices such as operations.

By applying the image processing device 10 to a video processing systemfor medical video, such as the medical video processing system 2,doctors can view the condition of an affected part and tissue on theperiphery thereof more accurately. In particular, when an extremelysmall camera such as an endoscope is used as the medical camera 21,there is a fixed limit on performance elements, such as the resolution,of the camera. Hence, when the image processing device 10 is applied tothis system and an output image acquired by improving the resolution ofthe input image is generated, even more remarkable effects are realized.Moreover, by applying the image processing device 10, real time videoprocessing that does not affect the implementation of medical practicessuch as operations can be realized.

FIGS. 6 and 7 are views illustrating the effects of the image processingdevice 10. FIG. 6(a) shows an image prior to image processing by themedical video processing system 2, and FIG. 6(b) is a view showing atwo-dimensional frequency spectrum thereof. Further, FIG. 7(a) shows animage following image processing by the medical video processing system2, and FIG. 7(b) is a view showing a two-dimensional frequency spectrumthereof. FIG. 7(c) is a view showing an increase in the two-dimensionalfrequency spectrum of FIG. 7(b) over that of FIG. 6(b). As is evidentfrom FIG. 7(c), white spots denoting the existence and strength offrequency components are spread over a wider range after imageprocessing is performed by the medical video processing system 2,indicating an increase in a high frequency component. In other words, itis evident that following image processing by the medical videoprocessing system 2, the resolution increases.

FIG. 8 is a conceptual diagram of an image transmission/reception system3 to which the image processing device 10 is applied. In the imagetransmission/reception system 3, transmission image data transmittedfrom a transmitter 5000 are received by a receiver 6000 over a networkor the like.

The transmitter 5000 includes an image data acquisition unit 5100, animage processing unit 5200, and a transmission processing unit 5300. Theimage data acquisition unit 5100 acquires image data generated byturning a predetermined image into digital data. The image dataacquisition unit 5100 may download the image data from a medium such asa CD-ROM or a DVD, or may acquire the image data via a USB cable, Wi-Fi,the Internet, a broadcasting network, and so on, for example. Further,the image data acquisition unit 5100 is not limited to means foracquiring image data from the outside of the transmitter 5000, andinstead, the image data acquisition unit 5100 itself may be constitutedby imaging means such as a camera. The image processing unit 5200includes filtering processing means, convolution processing means, andso on, for example. The transmission processing unit 5300 includes meansfor executing processing corresponding to a communication environmentand the like.

Next, an operation of the transmitter 5000 will be described briefly. Inthe transmitter 5000, the image processing unit 5200 executespredetermined image processing on original image data acquired by theimage data acquisition unit 5100. For example, the image processing unit5200 executes filtering processing on the original image data so as togenerate blurred image data from the original image data as thetransmission image data. In the blurred image data, the high frequencycomponent is reduced in comparison with the original image data, andtherefore the data can be reduced. Instead of generating blurred imagedata, transmission image data having a reduced data amount may begenerated from the original image data using another appropriate method.The transmission processing unit 5300 executes processing such asencryption in accordance with the communication environment and so on,and then transmits the transmission image data. Here, the communicationenvironment (the channel) includes the Internet, a mobile communicationnetwork, Wi-Fi, a broadcasting network, communication by a cable such asa USB, data exchange via a USB memory or an external memory, and so on.

The receiver 6000 includes, for example, a reception processing unit6100, a filter coefficient storage unit 6200, an image processing unit6300, and an image data output unit 6400. The reception processing unit6100 receives reception image data and executes processing such asdecryption thereon in accordance with the communication environment andso on. The filter coefficient storage unit 6200 stores a filtercoefficient for each pixel of the input image data to be subjected toimage processing. The image processing unit 6300 includes, for example,filtering processing means, convolution processing means, divisionprocessing means, and multiplication processing means. The image dataoutput unit 6400 outputs the output image data. The image data outputunit 6400 may write the image data to a medium such as a CD-ROM or aDVD, or may output the image data to a USB cable, Wi-Fi, the Internet, abroadcasting network, and so on, for example. Further, the image dataoutput unit 6400 is not limited to means for outputting image data tothe outside of the receiver 6000, and instead, the image data outputunit 6400 itself may be constituted by a monitor or the like.

Next, an operation of the receiver 6000 will be described briefly. Inthe receiver 6000, the reception processing unit 6100 executesprocessing such as decryption on the reception image data receivedthereby in accordance with the communication environment and so on. Theimage processing unit 6300 executes similar processing to that of theimage processing unit 300 according to the first to third embodimentsdescribed above, for example. The image data output unit 6400 outputsthe output image data.

By applying the present invention to an image transmission/receptionsystem in this manner, the data amount of the transmission data can bereduced in the transmitter, and an optimum image can begenerated/restored by the image processing executed in the receiver.

Example applications of the present invention were described above, butthe present invention is not limited to these example applications, andmay also be applied to a television video processing system, asurveillance camera video processing system, a telephoto imageprocessing system, another moving image or static image processingsystem, and so on, for example.

The embodiments described above were provided to facilitateunderstanding of the present invention and are not to be interpreted aslimiting the present invention. The present invention may bemodified/amended without departing from the spirit thereof, andequivalents of the present invention are included therein. In otherwords, embodiments acquired by a person skilled in the art by applyingappropriate design modifications to the above embodiments are includedin the scope of the present invention as long as these embodimentsinclude the features of the present invention. For example, therespective elements of the above embodiments, as well as thearrangements, materials, conditions, shapes, sizes, and so on thereof,are not limited to the examples described above, and may be modified asappropriate. Moreover, the above embodiments are examples, and may ofcourse be partially replaced by or combined with configurationsindicated by different embodiments. These embodiments are also includedin the scope of the present invention as long as the features of thepresent invention are included therein.

REFERENCE SIGNS LIST

-   1 Image processing system-   2 Medical video processing system-   Image transmission/reception system-   Image processing device-   Imaging camera-   Medical camera-   Display device-   Medical monitor-   100 Image data acquisition unit-   200 Filter coefficient storage unit-   300 Image processing unit-   310 Filtering processing unit-   320, 321, 322, 323 Convolution processing unit-   330, 331, 332, 333 Division processing unit-   340, 341, 342, 343 Multiplication processing unit-   350 Determination unit-   360 Buffer-   400 Image data output unit-   5000 Transmitter-   5100 Image data acquisition unit-   5200 Image processing unit-   5300 Transmission processing unit-   6000 Receiver-   6100 Reception processing unit-   6200 Filter coefficient storage unit-   6300 Image processing unit-   6400 Image data output unit

[Drawings]

-   [FIG. 1]-   20 IMAGING CAMERA

Input Image Data

-   10 IMAGE PROCESSING DEVICE

Output Image Data

-   30 DISPLAY DEVICE-   [FIG. 2]

Input Image Data

-   10 IMAGE PROCESSING DEVICE-   100 IMAGE DATA ACQUISITION UNIT-   300 IMAGE PROCESSING UNIT-   310 FILTERING PROCESSING UNIT-   320 CONVOLUTION PROCESSING UNIT-   330 DIVISION PROCESSING UNIT

What is claimed is:
 1. An image processing device comprising: filtercoefficient storing means storing a filter coefficient; means forexecuting filtering processing to generate first image data byperforming filtering on input image data; means for executingconvolution processing to generate second image data by performing aconvolution calculation on the first image data using the filtercoefficient stored in the filter coefficient storing means; means forexecuting division processing to generate third image data by dividingthe first image data by the second image data; and means for executingmultiplication processing to generate output image data by multiplyingthe third image data by the first image data.
 2. The image processingdevice according to claim 1, further comprising: means for executing theconvolution processing, the division processing, and the multiplicationprocessing repeatedly.
 3. The image processing device according to claim2, wherein the filter storing means stores a plurality of filtercoefficients, and the means for executing the convolution processinguses a different filter coefficient, among the plurality of filtercoefficients, each time the convolution processing is executed thereby.4. An image processing program for causing a computer to execute thesteps of: executing filtering processing to generate first image data byperforming filtering on input image data; executing convolutionprocessing to generate second image data by reading a filter coefficientstored in a filter coefficient storage unit and performing a convolutioncalculation on the first image data; executing division processing togenerate third image data by dividing the first image data by the secondimage data; and executing multiplication processing to generate outputimage data by multiplying the third image data by the first image data.5. An image processing method comprising the steps of: executingfiltering processing to generate first image data by performingfiltering on input image data; executing convolution processing togenerate second image data by reading a filter coefficient stored in afilter coefficient storage unit and performing a convolution calculationon the first image data; executing division processing to generate thirdimage data by dividing the first image data by the second image data;and executing multiplication processing to generate output image data bymultiplying the third image data by the first image data.
 6. An imagetransmission/reception system comprising: a transmitter for transmittingimage data; and a receiver for receiving the image data and processingthe image data, wherein the transmitter includes transmission imagegenerating means for generating transmission image data having a reduceddata amount from original image data, and the receiver includes: filtercoefficient storing means storing a filter coefficient; means forexecuting filtering processing to generate first image data byperforming filtering on input image data; means for executingconvolution processing to generate second image data by performing aconvolution calculation on the first image data using the filtercoefficient stored in the filter coefficient storing means; means forexecuting division processing to generate third image data by dividingthe first image data by the second image data; and means for executingmultiplication processing to generate output image data by multiplyingthe third image data by the first image data.
 7. An imagetransmission/reception method employed in an imagetransmission/reception system having a transmitter for transmittingimage data and a receiver for receiving the image data and processingthe image data, the method comprising the steps of: the transmitterexecuting the step of generating transmission image data having areduced data amount from original image data, and the receiver executingfiltering processing to generate first image data by performingfiltering on input image data; the receiver executing convolutionprocessing to generate second image data by reading a filter coefficientstored in a filter coefficient storage unit and performing a convolutioncalculation on the first image data; the receiver executing divisionprocessing to generate third image data by dividing the first image databy the second image data; and the receiver executing multiplicationprocessing to generate output image data by multiplying the third imagedata by the first image data.